GPU-Event-Mechanics Evaluation of Ice Impact Load Statistics
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The paper explores the use of a GPU-Event-Mechanics (GEM) simulation to assess local ice loads on a vessel operating in pack ice. The methodology uses an event mechanics concept implemented using massively parallel programming on a GPU enabled workstation. The simulation domain contains hundreds of discrete and interacting ice floes. A simple vessel is modeled as it navigates through the domain. Each ship-ice collision is modeled, as is every ice-ice contact. Each ship-ice collision event is logged, along with all relevant ice and ship data. Thousands of collisions are logged as the vessel transits many tens of kilometers of ice pack. The GEM methodology allows the simulations to be performed much faster than real time. The resulting impact load statistics are qualitatively evaluated and compared to published field data. The analysis provides insight into the nature of loads in pack ice. The work is part of a large research project at Memorial University called STePS2 (Sustainable Technology for Polar Ships and Structures).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it